我正在尝试使用Windows10上的xarray和python3.7从OpenDAP服务器下载一些数据,遍历了一系列的站点和年份,并编写了本地文件。下面的一个简单示例分别使用其中的两个,对我来说可能会失败:
import xarray as xr
stations = ["pxsc1","obxc1"]
for station in stations:
for year in ["2019","2020"]:
print(f"Working on station: {station} year: {year}")
ndbc_url = f"http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/{station}/{station}h{year}.nc"
print(ndbc_url)
fileout = "noaa_stdmet_{}_{}.nc".format(station,year)
print(fileout)
with xr.open_dataset(ndbc_url, engine='netcdf4') as remote:
remote.to_netcdf(fileout,format="NETCDF4_CLASSIC")第一个示例似乎运行正常,然后我得到HDF错误,如下所示。HDF5_USE_FILE_LOCKING的值似乎不会影响行为...我真的不理解这个限制,但我已经尝试过了。有没有其他方法可以让它工作呢?
Working on station: pxsc1 year: 2019
http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/pxsc1/pxsc1h2019.nc
noaa_stdmet_pxsc1_2019.nc
Working on station: pxsc1 year: 2020
http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/pxsc1/pxsc1h2020.nc
noaa_stdmet_pxsc1_2020.nc
Traceback (most recent call last):
File "F:\atmospheric\noaa\ndbc_xarray2.py", line 57, in <module>
ndbc_opendap()
File "F:\atmospheric\noaa\ndbc_xarray2.py", line 54, in ndbc_opendap
remote.to_netcdf(fileout,format="NETCDF4")
File "C:\Users\eli\miniconda3\envs\schimpy_env\lib\site-packages\xarray\core\common.py", line 1499, in __exit__
self.close()
File "C:\Users\eli\miniconda3\envs\schimpy_env\lib\site-packages\xarray\core\common.py", line 1294, in close
self._close()
File "C:\Users\eli\miniconda3\envs\schimpy_env\lib\site-packages\xarray\backends\netCDF4_.py", line 512, in close
self._manager.close(**kwargs)
File "C:\Users\eli\miniconda3\envs\schimpy_env\lib\site-packages\xarray\backends\file_manager.py", line 222, in close
file.close()
File "netCDF4\_netCDF4.pyx", line 2276, in netCDF4._netCDF4.Dataset.close
File "netCDF4\_netCDF4.pyx", line 2260, in netCDF4._netCDF4.Dataset._close
File "netCDF4\_netCDF4.pyx", line 1754, in netCDF4._netCDF4._ensure_nc_success
RuntimeError: NetCDF: HDF error发布于 2021-05-08 15:05:02
这似乎不是你的代码的问题,因为在我的电脑上一切都很好:
Working on station: pxsc1 year: 2019
http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/pxsc1/pxsc1h2019.nc
noaa_stdmet_pxsc1_2019.nc
Working on station: pxsc1 year: 2020
http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/pxsc1/pxsc1h2020.nc
noaa_stdmet_pxsc1_2020.nc
Working on station: obxc1 year: 2019
http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/obxc1/obxc1h2019.nc
noaa_stdmet_obxc1_2019.nc
Working on station: obxc1 year: 2020
http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/obxc1/obxc1h2020.nc
noaa_stdmet_obxc1_2020.nc然而,我认为这是因为计算能力有限。我假设Python仍然存储了第一个数组(它工作得很好),但没有足够的内存来存储第二个数组。这就是为什么它返回RuntimeError并可能重启内核(?)的原因。
尝试在with语句的末尾添加remote.close()。这可能会解决这个问题。
有必要使用NETCDF4_CLASSIC吗?我更喜欢使用NETCDF4,据我所知这更常见(?)。我怀疑这是否能解决你的问题,但你可以试一试。
下面是您的代码的一个稍微修改过的版本:
import xarray as xr
stations = ['pxsc1', 'obxc1']
year = [str(x) for x in range(2019,2020+1,1)]
url_base = 'http://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/'
files_in = [f"{url_base}{s}/{s}h{y}.nc" for s in stations for y in year]
files_out = [f"noaa_stdmet_{s}_{y}.nc" for s in stations for y in year]
def load(file, fileout):
print(f"open file: {file}")
with xr.open_dataset(file, engine='netcdf4') as remote:
print(f"writing file: {fileout}")
remote.to_netcdf(fileout, format="NETCDF4")
remote.close()
for fin, fout in list(zip(files_in, files_out)):
load(fin,fout)https://stackoverflow.com/questions/67393561
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